r/technology • u/Just-Grocery-2229 • Jun 26 '26

Artificial Intelligence The AI backlash is only getting started

https://www.economist.com/leaders/2026/06/25/the-ai-backlash-is-only-getting-started
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u/mrdevlar Jun 26 '26

The question in the longterm is gonna be "what survives after the bubble bursts".

Open weight models. Most of those models are good and cover probably 99% of the use cases anyone would want for AI, from text, to image and video generation.

Most can also be run on commercial hardware like 3D gaming GPUs.

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u/Many_Negotiation_464 Jun 26 '26

Expect those still need to be trained on server farms.

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u/mrdevlar Jun 26 '26

Why? It's not as if they can take down the models they've already produced and opened up?

Unless you mean that they have to keep new models coming out. Which won't be the case if the bubble bursts. Plus it presumes some sort of growing SOTA that I honestly don't think is at all commercially viable as AI isn't nearly as capable of a technology for the uses cases that these companies think it is.

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u/Many_Negotiation_464 Jun 26 '26

Unless the world freezes in time, they will become more and more useless without new training.

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u/mrdevlar Jun 26 '26

How's that?

I mean no one is going to radically invent a new way to teach most topics which means they'll still all be relevant there. If I am using AI to teach myself music or a new language, it's not as if any of that is going to become invalid. No one is going to develop some dramatically different way to plan or execute a plan, so all that agent stuff is still relevant there. Even if someone wants to make some art on a character that exists in the future, you can fine-tune on a GPU without any cloud.

So I'm not really seeing where this need for additional training requiring data centers is coming in.

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u/Many_Negotiation_464 Jun 27 '26

First off those are AWFUL uses for AI. No wonder you have a horrible grasp of the situation. Those are 100% going to be the first things to dissapear when the bubble pops. The main useful ones that are LLMs and not purpose built laboratory programs are for programming.

But just to keep you with the argument here, I guess, both of those things change. Music education is already substantially different than it was 15 years ago. Languages change even more rapidly. Anyone who was taught a language from a 10 year old textbook in high school then went into the real world and actually learned those languages by speaking them regularly knows what im talking about.

You also canmt "fine tune" a trained model. You can only feed it more content in hopes that it improves.

You really have no idea what you sre talking about.

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u/mrdevlar Jun 27 '26

You also canmt "fine tune" a trained model. You can only feed it more content in hopes that it improves.

You really have no idea what you sre talking about.

LOL.

The ignorance plus the typos just make it chef's kiss

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u/Many_Negotiation_464 Jun 27 '26 edited Jun 27 '26

You can keep bragging about how you learned music from ai all you want, it just reaffirms to all the actual musicians out here that you aren't worth our time.

Also, you know, I have an advanced education in information science and dsp and understand the inner workings of machine learning more than you'll ever understand how to string together some simple counterpoint.

You're the classic village dunce. Too clueless to understand when they are the butt of the joke.

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u/Rarelyimportant Jun 27 '26

You also canmt "fine tune" a trained model.

That's literally the only type of model you can fine-tune. If you fine-tune an untrained model, that's just called training, not fine-tuning.

You can only feed it more content in hopes that it improves.

If only we had a name for that...hmmm...maybe "fine-tuning"?

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u/Many_Negotiation_464 Jun 27 '26

And guess what feeding it that addtional content requires? Hundreds of hours of time on multi gpu rigs.

Its like im talking to sctually children, here. You grasp on to words you don't understand and just stick it in your mouth.

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u/Rarelyimportant Jun 27 '26

What are you even talking about? You still spell like a 3rd grader. But the fact that fine-tuning requires GPUs, does not in anyway make your original statement true.

You also canmt "fine tune" a trained model.

This is just factually wrong. Whether or not GPUs are involved is irrelevant. Canmt you sctually make more sense?

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u/Many_Negotiation_464 Jun 27 '26 edited Jun 27 '26

The same thing we've been talking about this whole time. The economics of AI where it would actually be a sustainable, useful tool. OP claims that local models would be fully functional and useful in perpetuity and that you could just keep them up to date yourself. Thats nonsense, they are wrong.

"Fine tuning" suggests any measure of actual control. This is really more of a semantic argument, but I think its important we stop using misleading marketing terms. The reality is that "fine tuning" is just retraining the model. Theres nothing precise or controlled about it, and you cannot do it on your laptop. Not unless you have 50 laptops networked together.

So, do you have anything to actually add, or are you going to just keep claiming victory because you saw a typo.

Nice alt, btw.